Computer Engineering and Applications ›› 2017, Vol. 53 ›› Issue (13): 227-234.DOI: 10.3778/j.issn.1002-8331.1601-0340

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Improved NSGA-II algorithm and its application in optimization of machining parameters

XU Jiangyan1, ZHONG Gaoyan1, YANG Shoufeng1,2   

  1. 1.College of Engineering, Nanjing Agricultural University, Nanjing 210031, China
    2.Faculty of Engineering and the Environments, University of Southampton, Southampton SO17 1BJ, UK
  • Online:2017-07-01 Published:2017-07-12



  1. 1.南京农业大学 工学院,南京 210031
    2.英国南安普顿大学 工程与环境学部,南安普顿 SO17 1BJ

Abstract: As some deficiencies such as uneven distribution of convergence in population, poor global searching ability, easily to run into partial optimization appeared in classic non-dominated sorting genetic algorithm II(NSGA-II), this paper proposes an improves algorithm by introducing orthogonal crossover strategy and hybrid mutation operator into the NSGA-II. The experiments on a series of test functions show that the improved NSGA-II has better performance than NSGA-II both in convergence and diversity. The research about optimization of processing parameters of 6061 aluminum alloy in precision turning based on improved algorithm and classic NSGA-II, reveal that the improved algorithm has better convergence rate and accuracy than the classic NSGA-II, which means the improved algorithm is more effective in solving the multi-objective optimization problems of machining parameters.

Key words: multi-objective optimization, processing parameters, NSGA-II algorithm, improved algorithm

摘要: 针对NSGA-II算法种群收敛分布不均匀,全局搜索能力差,易陷入局部最优等不足,引入正交交叉策略与混合变异算子,提出一种改进的NSGA-II算法。在测试函数上对改进NSGA-II算法与传统NSGA-II算法同时进行性能测试,结果表明改进的NSGA-II算法无论是在收敛性还是多样性上均优于NSGA-II算法。将改进算法与传统NSGA-II算法同时应用于6061铝合金精密车削加工参数多目标优化设计中,研究结果表明改进NSGA-II算法收敛精度更高,收敛速度更快,优化结果更加逼近全局最优解,在求解切削加工参数多目标优化问题时更加有效。

关键词: 多目标优化, 加工参数, NSGA-II算法, 改进算法